Health Care Data in the Public Domain: Empowering Patients

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The aggregation and utilization of data in health care has two sides, according to Lynn Gibson, vice president and CTO of Christus Health, Irving, California. The first, and most in focus, is the provider’s; the second, less emphasized but equally important, is the patient’s. “Health care is on a rapidly changing path,” he says, “and data-driven analysis is necessary for both the caregiver and the patient. We have to be able to collect the pertinent information to support both sides and make it available to both the patient and the clinician.”

Lynn GibsonThis, Gibson posits, is the duality at the root of health care’s current cultural conundrum: in focusing on providing data to both the patient and the clinician, providers can begin to break down what has historically been a very paternalistic approach to medicine. “When I look at the way my parents’ generation responded to physicians, it was compliant—whatever the doctor said, they would do, without question,” he explains. “Now my children, who are entering early adulthood, exhibit a very refined level of expectation and skepticism. As health care becomes more consumer-driven, this will be the biggest challenge we have to address.”

The Patient of the Future

The patient of the future, Gibson hypothesizes, will be a hyper-informed consumer of care who tracks his or her own health information; as evidence, he points to the increasing availability and popularity of smart phone and tablet apps designed for this very purpose. “As we have more and more analysis out there of physicians and hospitals, including quality and outcomes information, we’ll see more freedom of choice among patients,” he predicts. “They’re going to get to shop, and that level of patient empowerment will impact how physicians practice.”

For instance, he says, patients tracking their own medical history could see trends that would affect their tendency to access care. “If I’m a diabetic and can see my own blood sugar trends over time and map them against what I have eaten, or I’m a heart patient and can match my blood pressure cycles to the medication I’ve been taking, that’s incredibly empowering,” he says. “If I can see that for myself, why do I need to spend money to go into a physician’s office? It’s going to change what indications walk into the doors of our hospitals.”

In fact, Gibson says, this trend is already under way, as evidenced by the increase in care provided on an outpatient as opposed to an inpatient basis. “Most progressive hospital administrators now see that the more acute cases are what they are going to be managing in the future,” he notes. “When patients have the ability to monitor themselves and understand why they are feeling bad, they’ll make changes on their own to address that. Many patients are doing it already—our challenge, on the provider side, is to make sure they can do better with the information we give them.”

Challenges and Hurdles

Gibson says there are two key hurdles to surmounting that challenge: accuracy and timeliness of information. “Much of the information in electronic medical records is still input by hand by nurses, doctors, therapists,” he points out. “They’re recording their observations on everything from temperature to risk of fall, and there is the opportunity for transcription error or human error there.”

Timeliness is also a critical concern. “Most medical record information comes from transcriptions that occur much later in the process—for instance, radiologists read images, then do a transcription,” Gibson says. “With today’s technology, clinicians should be inputting information at least within the hour, but they have to change their work processes to accommodate that. Younger physicians, who used technology in medical school, are more adaptable to that than physicians who have been practicing for years in small community hospitals where the technology may be out of date. They may be more reluctant to change.”

Gibson points out that many health information systems utilize open-ended fields that are tricky, if not impossible, to map between platforms; he looks to the evolution of HL7 standards and the increasing sophistication of natural language processing tools to help address these issues, making data collection and sharing as accurate and timely as possible. “There’s no centralized gathering point yet for the information,” he says. “It’s becoming easier to export data out of these various systems, but the standards are not as tight as they